From Data to Knowledge, Wolfgang A. Gaul; Dietmar Pfeifer

Автор: Malley
Название: Statistical Learning for Biomedical Data
ISBN: 0521699096 ISBN-13(EAN): 9780521699099
Издательство: Cambridge Academ
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Описание: Biomedical researchers need machine learning techniques to make predictions such as survival/death or response to treatment when data sets are large and complex. This highly motivating introduction to these machines explains underlying principles in nontechnical language, using many examples and figures, and connects these new methods to familiar techniques.

Автор: Falmagne Jean-Claude
Название: Knowledge Spaces
ISBN: 3642353282 ISBN-13(EAN): 9783642353284
Издательство: Springer
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Описание: This book describes current applications and theory in knowledge spaces, including the bilingual ALEKS system, and its applications in mathematics and chemistry across the educational arc. Discusses knowledge spaces in teaching of college chemistry much more.

Автор: Saman K. Halgamuge; Lipo Wang
Название: Classification and Clustering for Knowledge Discovery
ISBN: 3642065422 ISBN-13(EAN): 9783642065422
Издательство: Springer
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Описание: This book covers recent advances in unsupervised and supervised data analysis methods in Computational Intelligence for knowledge discovery. If labeled data or data with known associations are available, we may be able to use supervised data analysis methods, such as classifying neural networks, fuzzy rule-based classifiers, and decision trees.

Автор: Eugene Roventa; Tiberiu Spircu
Название: Management of Knowledge Imperfection in Building Intelligent Systems
ISBN: 3540774629 ISBN-13(EAN): 9783540774624
Издательство: Springer
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Описание: This book is among the very few to be entirely dedicated to the treatment of knowledge imperfection when building intelligent systems. The authors are of the belief that an entire book should be focused on this important aspect of knowledge processing.

Автор: Pellegrini Tassilo
Название: Networked Knowledge - Networked Media
ISBN: 3642242553 ISBN-13(EAN): 9783642242557
Издательство: Springer
Цена: 27251.00 р.
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Автор: Martin Schader
Название: Analyzing and Modeling Data and Knowledge
ISBN: 3540547088 ISBN-13(EAN): 9783540547082
Издательство: Springer
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Описание: This volume encapsulates the papers presented at a conference on the classification of data held in 1991. The material is organized in three parts - data analysis and classification, data modelling and knowledge processing and applications and special subjects.

Автор: Chenyi Hu; R. Baker Kearfott; Andre de Korvin; Vla
Название: Knowledge Processing with Interval and Soft Computing
ISBN: 1849967849 ISBN-13(EAN): 9781849967846
Издательство: Springer
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Описание: Interval computing combined with fuzzy logic is an emerging tool in studying artificial intelligence and knowledge processing (AIKP) applications. This accessible book, a must-read for those in AI, provides introductions for both interval and fuzzy computing.

Автор: Berthold Lausen; Sabine Krolak-Schwerdt; Matthias
Название: Data Science, Learning by Latent Structures, and Knowledge Discovery
ISBN: 366244982X ISBN-13(EAN): 9783662449820
Издательство: Springer
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Описание: This volume comprises papers dedicated to data science and the extraction of knowledge from many types of data: structural, quantitative, or statistical approaches for the analysis of data;

Автор: Hans-Hermann Bock; Peter Ihm
Название: Classification, Data Analysis, and Knowledge Organization
ISBN: 3540534830 ISBN-13(EAN): 9783540534839
Издательство: Springer
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Описание: Proceedings of the 14th Annual Conference of the Gesellschaft fur Klassifikation e.V., University of Marburg March 12-14, 1990

Автор: O. Maimon; M. Last
Название: Knowledge Discovery and Data Mining
ISBN: 1441948422 ISBN-13(EAN): 9781441948427
Издательство: Springer
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Цена: 19559.00 р.
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Описание: This book presents a specific and unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network methodology. Data Mining (DM) is the science of modelling and generalizing common patterns from large sets of multi-type data. DM is a part of KDD, which is the overall process for Knowledge Discovery in Databases. The accessibility and abundance of information today makes this a topic of particular importance and need. The book has three main parts complemented by appendices as well as software and project data that are accessible from the book's web site (http: //www.eng.tau.ac.iV-maimonlifn-kdg ). Part I (Chapters 1-4) starts with the topic of KDD and DM in general and makes reference to other works in the field, especially those related to the information theoretic approach. The remainder of the book presents our work, starting with the IFN theory and algorithms. Part II (Chapters 5-6) discusses the methodology of application and includes case studies. Then in Part III (Chapters 7-9) a comparative study is presented, concluding with some advanced methods and open problems. The IFN, being a generic methodology, applies to a variety of fields, such as manufacturing, finance, health care, medicine, insurance, and human resources. The appendices expand on the relevant theoretical background and present descriptions of sample projects (including detailed results).